Authors : V. Magudeeswaran, P. Thirumurugan and S. Bharath
Abstract: Histogram Equalization (HE) is one of the most popular methods for improving contrast in digital images. As a result, such image creates side-effects such as washed-out appearance and false contouring due to the significant change in brightness. To overcome these problems mean brightness preserving HE based techniques have been proposed. Generally, these methods partition the histogram of the original image into sub histograms and then independently equalize each sub-histogram. This study presents a simple histogram modification framework for still image contrast enhancement to improve image contrast without making any loss in image details. The proposed method consists of two stages. First, histogram of the original image is modified with respect to uniform histogram. In the second stage, the modified histogram of the original image is separated into two sub-histograms based on the mean of the original image and then equalizes them independently to preserve image brightness. By introducing the enhancement parameter, the level of the contrast enhancement can be adjusted based on the input image contrast. The experimental results show that it preserves more brightness and produces natural looking images than the other conventional methods. The proposed method has been tested using several images and gives better visual quality as compared to several other methods.
V. Magudeeswaran, P. Thirumurugan and S. Bharath, 2016. Histogram Modification Framework for Image Contrast Enhancement and Brightness Preserving. Asian Journal of Information Technology, 15: 217-222.